Abstract
This article proposes an intuitionistic fuzzy (IF) Elimination and Choice Translating Reality (ELECTRE) method to rank consumers’ alternatives ranking order with subjects’ questionnaires by using IF data and the ranking order applied the proposed method are closer to consumers their own ranking order. Moreover, the mean value of Spearman correlation coefficients are higher than 80% in each product category, and also higher than 90% at bank service product category especially. This study uses IF sets characteristics to handle uncertain decision environment and to classify the concordance and discordance sets according to their score function for measuring the degree of suitability of each alternative and also using the concept of the positive and negative ideal solutions to rank all candidate alternatives in the proposed method. Furthermore, analyzer can use this method to gain valuable information from questionnaires, and consumers rarely provide preference data directly. Additionally, an empirical study is given to illustrate the proposed method and also compared with Wu and Chen 2011’s paper which considered not only score function but also accuracy function. The results show that using the proposed method, decision makers can easily predict candidate alternatives ranking order and make decisions accurately.
Highlights
Customers’ preference and intention are important market survey subjects which will influence some marketing strategies for better outcome and finding the potential market and customers for companies in a rapidly changing business environment
The main purpose of this paper is to further extend ELECTRE method to solve multicriteria decision making (MCDM) problems in intuitionistic fuzzy (IF) environments according to score function for measure the degree of suitability of evaluations
There are many meticulous type-2 Fuzzy ELECTRE methods which are proposed by outstanding authors to solve decision making problems
Summary
Customers’ preference and intention are important market survey subjects which will influence some marketing strategies for better outcome and finding the potential market and customers for companies in a rapidly changing business environment. These commerce data can be collected from official data [1], questionnaire [2], [3], social media [4], e-commerce websites [5], [6], transactional data [7], or existing studies [8] etc.
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More From: European Journal of Engineering Research and Science
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